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Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback

Published: 06 July 2017 Publication History
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  • Abstract

    This paper presents an age-friendly system for improving the elderly's online shopping experience. Different from most related studies focusing on website design and content organization, we propose to integrate three assistive techniques to facilitate the elderly's browsing of products in E-commerce platforms, including the crowd-improved speech recognition, the multimodal search, and the personalized speech feedback. The first two techniques, namely, the crowd-improved speech recognition and the multimodal search, work together to allow the elderly search for desired products flexibly using either speech, an image, text, or any combination of them whichever are convenient for the elderly. The personalized speech feedback provides a speech summary of search result in a personalized voice. That is, the elderly are allowed to choose or even create their desired voices, and also can customize the voices in terms of pitch, speaking speed, and loudness. As a whole, the proposed system is expected to help and engage the elderly's E-commerce adoption. Testing on real-world E-commerce product datasets demonstrated the usability of the proposed system.

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    • (2021)Enhancing the Low Adoption Rate of M-commerce in Nigeria Through Yorùbá Voice TechnologyHybrid Intelligent Systems10.1007/978-3-030-73050-5_52(516-524)Online publication date: 17-Apr-2021
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    1. Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback

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          cover image ACM Other conferences
          ICCSE'17: Proceedings of the 2nd International Conference on Crowd Science and Engineering
          July 2017
          158 pages
          ISBN:9781450353755
          DOI:10.1145/3126973
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          Publication History

          Published: 06 July 2017

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          Author Tags

          1. Age-friendly E-commerce
          2. Crowd-improved speech recognition
          3. Multimodal search
          4. Personalized speech feedback
          5. enhanced user browsing

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          ICCSE'17 Paper Acceptance Rate 24 of 66 submissions, 36%;
          Overall Acceptance Rate 92 of 247 submissions, 37%

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          View all
          • (2023)Multi-channel Attentive Weighting of Visual Frames for Multimodal Video Classification2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10192036(1-8)Online publication date: 18-Jun-2023
          • (2021)User-Generated Content Analysis for Customer Needs ElicitationData-Driven Engineering Design10.1007/978-3-030-88181-8_2(23-40)Online publication date: 10-Oct-2021
          • (2021)Enhancing the Low Adoption Rate of M-commerce in Nigeria Through Yorùbá Voice TechnologyHybrid Intelligent Systems10.1007/978-3-030-73050-5_52(516-524)Online publication date: 17-Apr-2021
          • (2018)Usability Analysis of the Novel Functions to Assist the Senior Customers in Online ShoppingSocial Computing and Social Media. User Experience and Behavior10.1007/978-3-319-91521-0_14(173-185)Online publication date: 31-May-2018
          • (2017)Novel Functional Technologies for Age-Friendly E-commerceHuman Aspects of IT for the Aged Population. Applications, Services and Contexts10.1007/978-3-319-58536-9_13(150-158)Online publication date: 14-May-2017

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